Remote structural health monitoring with serially multiplexed fiber optic acoustic emission sensors

Development and testing of a serially multiplexed fiber optic sensor system is described.The sensor differs from conventional fiber optic acoustic systems,as it is capable of sensing AE emissions at several points along the length of a single fiber.Multiplexing provides for single channel detection of cracks and their locations in large structural systems. An algorithm was developed for signal recognition and tagging of the AE waveforms for detection of' crack locations,Labora- tory experiments on plain concrete beams and post-tensioned FRP tendons were pcrlormed to evaluate the crack detection capability of the sensor system.The acoustic emission sensor was able to detect initiation,growth and location of the cracks in concrete as well as in the FRP tendons.The AE system is potentially suitable lot applications involving health monitoring of structures following an earthquake.

Acoustic emission monitoring of rockbursts during TBM-excavated headrace tunneling at Jinping Ⅱ hydropower station

To better understand the mechanical properties of marble at Jinping II hydropower station, this paper examines the changes of brittle rocks in excavation damaged zones(EDZs) before and after excavation of tunnel with the tunnel boring machine(TBM). The paper attempts to employ the acoustic emission(AE) to study the AE characteristics and distribution of rockburst before and after TBM-excavated tunnel. It is known that the headrace tunnel #2, excavated by the drill-and-blast(D&B) method, is ahead of the headrace tunnel #3 that is excavated by TBM method. The experimental sub-tunnel #2–1, about 2000 m in depth and 13 m in diameter, between the two tunnels is scheduled. In the experimental sub-tunnel #2–1, a large number of experimental boreholes are arranged, and AE sensors are installed within 10 m apart from the wall of the headrace tunnel #3. By tracking the microseismic signals in rocks, the location, frequency, quantity, scope and intensity of the microseismic signals are basically identifed. It is observed that the AE signals mainly occur within 5 m around the rock wall, basically lasting for one day before tunnel excavation and a week after excavation. Monitoring results indicate that the rockburst signals are closely related to rock stress adjustment. The rock structure has a rapid self-adjustment capacity before and after a certain period of time during tunneling. The variations of rock stresses would last for a long time before reaching a fnal steady state. Based on this, the site-specifc support parameters for the deep tunnels can be accordingly optimized.

Acoustic Emission Monitoring and Microscopic Investigation of Cracks in ERCuNi Cladding

A corrosion resistant CuNi cladding was deposited on SM45C (equivalent to AISI1045) substrate by DC inverse arc welding. During the welding process, a three channel acoustic emission (AE) monitoring system was applied to detect the crack signals generating from both the cladding process and after cladding. Characteristics of the welding crack signal and noise signal had been analyzed systematically. Based on the record time of the signal, the solidification crack and delayed crack were distinguished. By two-dimensional AE source location, the crack position was located, and then investigated by scanning electron microscopy (SEM). Results showed that the AE system could detect the welding crack with high sensitivity and the two-dimensional source location could accurately determine the crack position. Microstructures of the cladding and heat affected zone (HAZ) were examined. Dendrites in the cladding and coarse grains in the HAZ were found.

Distributed optical fiber acoustic sensor for in situ monitoring of marine natural gas hydrates production for the first time in the Shenhu Area,China

The distributed acoustic sensor(DAS)uses a single optical cable as the sensing unit,which can capture the acoustic and vibration signals along the optical cable in real-time.So it is suitable for monitoring downhole production activities in the process of oil and gas development.The authors applied the DAS system in a gas production well in the South China Sea for in situ monitoring of the whole wellbore for the first time and obtained the distributed acoustic signals along the whole wellbore.These signals can clearly distinguish the vertical section,curve section,and horizontal production section.The collected acoustic signal with the frequency of approximately 50 Hz caused by the electric submersible pump exhibit a signal-to-noise ratio higher than 27 dB.By analyzing the acoustic signals in the production section,it can be located the layers with high gas production rates.Once an accurate physical model is built in the future,the gas production profile will be obtained.In addition,the DAS system can track the trajectory of downhole tools in the wellbore to guide the operation.Through the velocity analysis of the typical signals,the type of fluids in the wellbore can be distinguished.The successful application of the system provides a promising whole wellbore acoustic monitoring tool for the production of marine gas hydrate,with a good application prospect.

Research on the Monitoring System of CNC Grinding Process Based on Acoustic Emission

Using on-line monitoring during the CNC grinding process,the hazard case such as the crushing of grinding wheel and various safety accidents could be avoided,and the optimum time for dressing and replacing grinding wheel could also be determined,and hence,the service life of the grinding wheel could be prolonged and grinding quality could be improved. To overcome the limitation of some traditional techniques in which some parameters including the grinding power and force,torque and so on were monitored,the acoustic emission (AE) technique,which provides high sensitivity and responding speed,were developed in the present paper. The mechanism of AE during grinding was reviewed. Moreover,a virtual AE monitoring system,which could monitor the grinding state under different working conditions during the grinding,has been developed based on the Virtual Instruments technique. Some experiments were also performed on the internal grinder. The results showed that the AE signals became stronger with increasing the main shaft speed and grinding depth or decreasing the distance between the AE sensor and grinding area.

Influence Analysis on the Floating Underwater Monitoring System Applicable for Very-Low-Frequency Acoustic Measurement

Ocean vector acoustic measurement is feasible affected by the hydrodynamic interference caused by the flow fluctuations and structural vibrations, especially in the very-low-frequency monitoring. Hence, a novel horizontal floating platform including a horizontal floating cable, vertical mooring cable and floating main body is proposed and described in this paper. It has the advantages of good maneuverability along with the current and multi-stage vibration isolation. The main application of this platform is to measure the ocean ambient noise coming from the wave fluctuation and the deterministic acoustic signals such as aquatic organisms, underwater targets and sailing vehicles. The influence of the current fluctuation on the attitude angle and flow induced vibration of cables and main body are analyzed with some previous sea test data. Moreover, the comparison between the vertical type platform used before and the horizontal type platform is also discussed. It is concluded that there is obvious relevance between the attitude angle and ocean current variation. Meanwhile, the abnormal influence on the main body is caused by the vibration transmission from the fluctuation of cables. There will be the influence on the accuracy of the acoustic measurement above 100 Hz, and the inherent vibration characteristic of the main body is the primary reason.

Experimental Study of Acoustic Noise Correlation Technique for Passive Monitoring of Rails

The work presented in this paper aims at investigating the ability of acoustic noise correlation technique for railway infrastructure health monitoring. The principle of this technique is based on impulse responses reconstruction by correlation of random noise propagated in the medium. Since wheel-rail interaction constitutes a source of such noise, correlation technique could be convenient for detection of rail defects using only passive sensors. Experiments have been carried out on a 2 m-long rail sample. Acoustic noise is generated in the sample at several positions. Direct comparison between an active emission-reception response and the estimated noise correlation function has confirmed the validity of the equivalence relation between them. The quality of the reconstruction is shown to be strongly related to the spatial distribution of the noise sources. High sensitivity of the noise-correlation functions to a local defect on the rail is also demonstrated. However, interpretation of the defect signature is more ambiguous than when using classical active responses. Application of a spatiotemporal Fourier transform on data recorded with variable sensor-defect distances has allowed overcoming this ambiguity.

New Improvement for Monitoring Small Drill Breakage with Acoustic Emission

The risk of fracture is higher in the case of small diameter drills than that with any other cutting tools Analysis of cutting forces or motor current is fundamentally unsuitable for practical applications to the detection of small drlls, owing to the low sensitivity and less parameter variation involved[1] Suitably located AE (Acoustic Emission )sensor can, however, be used to obtain signals which allow tool fracture to be monitored. The monitoring system developed in this study employs a new conducting medium and a signal processing method in a suitable frequence band,which not only solves the installation problem of AE sensor, but also largely improves the reliability of the tool fracture monitoring system.

Damage evaluation of notched aluminum alloy and weld based on acoustic emission and digital image monitoring

Acoustic emission （ AE ） features during the fracture process of notched wrought aluminum alloy 7N01 and weld were investigated under the three-point bending load. Wavelet transform is used to investigate the time-frequency features of AE signals during the test. The experimental results showed that AE energy was effective indicators to detect the crack initiation for 7N01 aluminum. The digital images from monitoring the notch tip region of 7 NO1 aluminum sample verify the prediction of AE signals. The weld emits low energy, weak signal strength, and low peak amplitude, while stronger AE energy, amplitude, and more AE event counts for the base metal. In short, the AE technique was more sensitive to the changes in the fracture mode and could be used to monitor the damage development in welded structures.

Event-Driven Non-Intrusive Load Monitoring Algorithm Based on Targeted Mining Multidimensional Load Characteristics

Nowadays,the advancement of nonintrusive load monitoring(NILM)has been hastened by the ever-increasing requirements for the reasonable use of electricity by users and demand side management.Although existing researches have tried their best to extract a wide variety of load features based on transient or steady state of electrical appliances,it is still very difficult for their algorithm to model the load decomposition problem of different electrical appliance types in a targeted manner to jointly mine their proposed features.This paper presents a very effective event-driven NILM solution,which aims to separately model different appliance types to mine the unique characteristics of appliances from multi-dimensional features,so that all electrical appliances can achieve the best classification performance.First,we convert the multi-classification problem into a serial multiple binary classification problem through a pre-sort model to simplify the original problem.Then,ConTrastive Loss K-Nearest Neighbour(CTLKNN)model with trainable weights is proposed to targeted mine appliance load characteristics.The simulation results show the effectiveness and stability of the proposed algorithm.Compared with existing algorithms,the proposed algorithm has improved the identification performance of all electrical appliance types.

The Peculiarities of Acoustical Monitoring of Moving Objects in Shallow Water Areas

The article considers peculiarities of underwater monitoring of moving objects in the shallow water areas, particularly seaports. These areas are characterized by a multitude of factors influencing the efficiency of detection. Nonstationarity conditions of sound propagation and specific interference caused by shipping are the major factors. The various algorithms for the space-time signal processing have been tested and some experimental results are presented. It has been shown that the use of clipped mode in conjunction with the correlation processing of wideband signals and subsequent speckle tracking allow realizing high efficiency of monitoring.

Identification of Antarctic minke and killer whales with passive acoustic monitoring in Prydz Bay, Antarctica

Although four species of odontocete and four species of baleen whale have been recorded in Prydz Bay,their vocalizations have been rarely investigated.Underwater vocalizations were recorded during March 2017 in Prydz Bay,Antarctica.Bio-duck sounds,downsweeps,inverted“u”shape signals,whistles,pulsed sounds,and broadband clicks were recorded.Bio-duck sounds and downsweeps were associated with Antarctic minke whales(Balaenoptera bonaerensis)based on visual observations.Similarities between inverted“u”shape signals,biphonic calls,and clicks with vocalizations previously described for killer whales(Orcinus orca)lead us believe the presence of Antarctic killer whales.According to sound structures,signal characteristics,and recording location,Antarctic type C killer whales were the most probable candidates to produce these detected calls.These represent the fi rst detection of inverted“u”shape signals in Antarctic waters,and the fi rst report of Antarctic killer whale in Prydz Bay based on passive acoustic monitoring.The co-existence of Antarctic minke and killer whales may imply that minke whales can detect diff erences between the sounds of mammal-eating and fi sh-eating killer whales.Our descriptions of these underwater vocalizations contribute to the limited body of information regarding the distribution and acoustic behavior of cetaceans in Prydz Bay.

Wireless environmental monitoring system for transformer substation based on acoustic sensor

In this paper, an indoor environmental monitoring solution is proposed for the transformer sub- station system by using the ZigBee technology. It mainly analyzes the principle of sulfur hexafluoride sensor based on the acoustic method and puts forward a difference data processing method of single- channel and temperature compensation point at power consumption issues for sensor detection. The method not only reduces the sensor power consumption, but also ensures the accuracy and extends the lifetime of wireless sensor nodes effectively. This paper also analyzes the design of the base sta- tion mode, and demonstrates the running processes of routers and sensors. The feasibility of the pro- posed approach has been testified and proved.

Design, Implementation and Simulation of Non-Intrusive Sensor for On-Line Condition Monitoring of MV Electrical Components

Non-intrusive measurement technology is of great interest for the electrical utilities in order to avoid an interruption in the normal operation of the supply network during diagnostics measurements and inspections. Inductively coupled electromagnetic sensing provides a possibility of non-intrusive measurements for online condition monitoring of the electrical components in a Medium Voltage (MV) distribution network. This is accomplished by employing Partial Discharge (PD) activity monitoring, one of the successful methods to assess the working condition of MV components but often requires specialized equipment for carrying out the measurements. In this paper, Rogowski coil sensor is presented as a robust solution for non-intrusive measurements of PD signals. A high frequency prototype of Rogowski coil is designed in the laboratory. Step-by-step approach of constructing the sensor system is presented and performance of its components (coil head, damping component, integrator and data acquisition system) is evaluated using practical and simulated environments. Alternative Transient Program-Electromagnetic Transient Program (ATP-EMTP) is used to analyze the designed model of the Rogowski coil. Real and simulated models of the coil are used to investigate the behavior of Rogowski coil sensor at its different stages of development from a transducer coil to a complete measuring device. Both models are compared to evaluate their accuracy for PD applications. Due to simple design, flexible hardware, and low cost of Rogowski coil, it can be considered as an efficient current measuring device for integrated monitoring applications where a large number of sensors are required to develop an automated online condition monitoring system for a distribution network.

Partial Discharge Simulations Used for the Design of a Non-Intrusive Cable Condition Monitoring Technique

The purpose of this paper is to investigate the effect of PD （partial discharge） activity within medium voltage XLPE （cross-linked polyethylene） cables. The effect of partial discharge was studied by means of a number of simulations. The simulations were based on the well-known three capacitor model for partial discharge. An equivalent circuit was derived for partial discharge due to a single void in the insulation material of a power cable. The results obtained from the simulations will form the basis of the design proses of a non-intrusive condition monitoring technique. The technique is based on the classification of discharge activity according to five levels of PD. Future work will include the improvement of the simulation model by investigating the high frequency model of a power cable as well as the statistical nature of PD activity. This will improve the accuracy of the simulation results when compared to actual measurements. The work discussed in this paper will be used to construct and calibrate a practical model which will make use of PD measurements for non-intrusive condition monitoring of medium voltage electrical cables.

Rolling Bearing Condition Monitoring Technique Based on Cage Rotation Analysis and Acoustic Emission

In this paper,we present an alternative technique for detecting changes in the operating conditions of rolling element bearings(REBs)that can lead to premature failure.The developed technique is based on measuring the kinematics of the bearing cage.The rotational motion of the cage is driven by traction forces generated in the contacts of the rolling elements with the races.It is known that the cage angular frequency relative to shaft angular frequency depends on the bearing load,the bearing speed,and the lubrication condition since these factors determine the lubricant film thickness and the associated traction forces.Since a large percentage of REB failures are due to misalignment or lubrication problems,any evidence of these conditions should be interpreted as an incipient fault.In this paper,a novel method for the measurement of the instantaneous angular speed(IAS)of the cage is developed.The method is evaluated in a deep groove ball bearing test rig equipped with a cage IAS sensor,as well as a custom acoustic emission(AE)transducer and a piezoelectric accelerometer.The IAS of the cage is analyzed under different bearing loads and shaft speeds,showing the dependence of the cage angular speed with the calculated lubricant film thickness.Typical bearing faulty operating conditions(mixed lubrication regime,lubricant depletion,and misalignment)are recreated.It is shown that the cage IAS is dependent on the lubrication regime and is sensitive to misalignment.The AE signal is also used to evaluate the lubrication regime.Experimental results suggest that the proposed technique can be used as a condition monitoring tool in industrial environments to detect abnormal REB conditions that may lead to premature failure.

Study on Acoustic Emission Characteristics of Deformation Damage Process of Zirconia Ceramics

Zirconia ceramics have become increasingly widely used in recent years and are favored by relevant enterprises. From the traditional dental field to aerospace, parts manufacturing has been used, but there is limited research on the deformation and damage process of zirconia ceramics. This article analyzes the acoustic emission characteristics of each stage of ceramic damage from the perspective of acoustic emission, and explores its deformation process characteristics from multiple perspectives such as time domain, frequency, and EWT modal analysis. It is concluded that zirconia ceramics exhibit higher brittleness and acoustic emission strength than alumina ceramics, and when approaching the fracture, it tends to generate lower frequency acoustic emission signals.

APPLICATION OF ACOUSTIC EMISSION SENSOR IN DETECTING TOOL BREAKAGE IN MICRO-MILLING

Acoustic emission （AE） sensors are used to monitor tool conditions in micro-milling operations. Together with the microphone, the AE sensor can detect the tool breakage more accurately and more effectively by applying the wavelet analysis. The processed tool breakage technique by AE sensor is used to perform the wavelet analysis on the experimental data. Results indicate the feasibility of using the AE signals for monitoring the tool condition in micro-milling.

AN INTELLIGENT TOOL CONDITION MONITORING SYSTEM USING FUZZY NEURAL NETWORKS

Reliable on line cutting tool conditioning monitoring is an essential feature of automatic machine tool and flexible manufacturing system (FMS) and computer integrated manufacturing system (CIMS). Recently artificial neural networks (ANNs) are used for this purpose in conjunction with suitable sensory systems. The present work in Norwegian University of Science and Technology (NTNU) uses back propagation neural networks (BP) and fuzzy neural networks (FNN) to process the cutting tool state data measured with force and acoustic emission (AE) sensors, and implements a valuable on line tool condition monitoring system using the ANNs. Different ANN structures are designed and investigated to estimate the tool wear state based on the fusion of acoustic emission and force signals. Finally, four case studies are introduced for the sensing and ANN processing of the tool wear states and the failures of the tool with practical experiment examples. The results indicate that a tool wear identification system can be achieved using the sensors integration with ANNs, and that ANNs provide a very effective method of implementing sensor integration for on line monitoring of tool wear states and abnormalities.

On-Line Monitoring of Cutting Tool Fracture & Wear

A technique of detecting cutting tool fracture and ultimate wear by si- multaneously monitoring both the spindle motor current and cutting process related acoustic emission(AE)in the cutting process is reported.The technique can detect breakage of drills having diameter over 0.8mm,turning cutter crack of area over 0.2mm,and the ultimate wear.The principle,system construction,experimental method and result of the technique are discussed.The ratio of success in detection approaches 96% or higher.